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Patrick Thiam
Patrick Thiam
Institute of Neural Information Processing, Ulm University, Germany
Verified email at uni-ulm.de
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Year
Adaptive confidence learning for the personalization of pain intensity estimation systems
M Kächele, M Amirian, P Thiam, P Werner, S Walter, G Palm, ...
Evolving Systems 8, 71-83, 2017
852017
Methods for person-centered continuous pain intensity assessment from bio-physiological channels
M Kächele, P Thiam, M Amirian, F Schwenker, G Palm
IEEE Journal of Selected Topics in Signal Processing 10 (5), 854-864, 2016
822016
The senseemotion database: A multimodal database for the development and systematic validation of an automatic pain-and emotion-recognition system
M Velana, S Gruss, G Layher, P Thiam, Y Zhang, D Schork, V Kessler, ...
Multimodal Pattern Recognition of Social Signals in Human-Computer …, 2017
742017
Multimodal data fusion for person-independent, continuous estimation of pain intensity
M Kächele, P Thiam, M Amirian, P Werner, S Walter, F Schwenker, ...
Engineering Applications of Neural Networks: 16th International Conference …, 2015
702015
Multi-Modal Pain Intensity Recognition Based on the SenseEmotion Database
P Thiam, V Kessler, M Amirian, P Bellmann, G Layher, Y Zhang, M Velana, ...
IEEE Transactions on Affective Computing 12 (3), 743-760, 2019
682019
Exploring Deep Physiological Models for Nociceptive Pain Recognition
P Thiam, P Bellmann, HA Kestler, F Schwenker
Sensors 19 (20), 4503, 2019
592019
Ensemble methods for continuous affect recognition: Multi-modality, temporality, and challenges
M Kächele, P Thiam, G Palm, F Schwenker, M Schels
Proceedings of the 5th International Workshop on Audio/Visual Emotion …, 2015
442015
Two-stream attention network for pain recognition from video sequences
P Thiam, HA Kestler, F Schwenker
Sensors 20 (3), 839, 2020
352020
Multi-classifier-systems: architectures, algorithms and applications
P Bellmann, P Thiam, F Schwenker
Computational Intelligence for Pattern Recognition, 83-113, 2018
332018
Multi-modal data fusion for pain intensity assessment and classification
P Thiam, F Schwenker
2017 Seventh International Conference on Image Processing Theory, Tools and …, 2017
322017
Multimodal Deep Denoising Convolutional Autoencoders for Pain Intensity Classification based on Physiological Signals.
P Thiam, HA Kestler, F Schwenker
ICPRAM, 289-296, 2020
272020
Multi-modal pain intensity assessment based on physiological signals: A deep learning perspective
P Thiam, H Hihn, DA Braun, HA Kestler, F Schwenker
Frontiers in Physiology 12, 720464, 2021
262021
Pain recognition with camera photoplethysmography
V Kessler, P Thiam, M Amirian, F Schwenker
2017 Seventh International Conference on Image Processing Theory, Tools and …, 2017
252017
Audio-visual recognition of pain intensity
P Thiam, V Kessler, S Walter, G Palm, F Schwenker
Multimodal Pattern Recognition of Social Signals in Human-Computer …, 2017
232017
Hierarchical Combination of Video Features for Personalised Pain Level Recognition.
P Thiam, V Kessler, F Schwenker
ESANN, 465-470, 2017
222017
Detection of emotional events utilizing support vector methods in an active learning HCI scenario
P Thiam, S Meudt, M Kächele, G Palm, F Schwenker
Proceedings of the 2014 workshop on emotion representation and modelling in …, 2014
172014
Multimodal fusion including camera photoplethysmography for pain recognition
V Kessler, P Thiam, M Amirian, F Schwenker
2017 International Conference on Companion Technology (ICCT), 1-4, 2017
152017
Continuous multimodal human affect estimation using echo state networks
M Amirian, M Kächele, P Thiam, V Kessler, F Schwenker
Proceedings of the 6th International Workshop on Audio/Visual Emotion …, 2016
152016
A temporal dependency based multi-modal active learning approach for audiovisual event detection
P Thiam, S Meudt, G Palm, F Schwenker
Neural Processing Letters 48 (2), 709-732, 2018
142018
On annotation and evaluation of multi-modal corpora in affective human-computer interaction
M Kächele, M Schels, S Meudt, V Kessler, M Glodek, P Thiam, ...
Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction …, 2015
132015
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